Evolution of female preference for younger males.

Abstract

Previous theoretical work has suggested that females should prefer to mate with older males, as older males should have higher fitness than the average fitness of the cohort into which they were born. However, studies in humans and model organisms have shown that as males age, they accumulate deleterious mutations in their germ-line at an ever-increasing rate, thereby reducing the quality of genes passed on to the next generation. Thus, older males may produce relatively poor-quality offspring. To better understand how male age influences female mate preference and offspring quality, we used a genetic algorithm model to study the effect of age-related increases in male genetic load on female mate preference. When we incorporate age-related increases in mutation load in males into our model, we find that females evolve a preference for younger males. Females in this model could determine a male's age, but not his inherited genotype nor his mutation load. Nevertheless, females evolved age-preferences that led them to mate with males that had low mutation loads, but showed no preference for males with respect to their somatic quality. These results suggest that germ-line quality, rather than somatic quality, should be the focus of female preference in good genes models.

Mutation probability increased either as a linear (A, C, E) or as a cubic (B, D, F) function of male age. Values represent the mean±1 standard error among eight replicate simulations after 320,000 cycles. Dashed line is the value for female preference expected by chance alone.

Mutation probability increased either as a linear (A, C) or as a cubic (B, D) function of male age. Relationships based on eight replicate simulations of 320,000 cycles across all ten age classes (N = 80). Based on partial correlation analyses, all relationships are significant except when the maximum mutation rate was 0.01. For clarity, individual data points were ranked by the independent variable and placed in bins of ten. The data points on the graphs represent the averages of the individual data points with each bin. The regression lines are based on all 80 data points for a given mutation rate. Constant (solid line), max = 0.01 (dotted line), max = 0.05 (dashed line), max = 0.1 (dashed and dotted line).